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Not Always a Black Box: Machine Learning Approaches For Model Explainability
What is model explainability? Imagine that you have built a very precise machine learning model by using clever tricks and non-standard features. You are beyond happy and proud. However, when you present your results to your stakeholders, they are less thrilled. They don’t understand what you did and why.... Read more
Bias Variance Decompositions using XGBoost
This blog dives into a theoretical machine learning concept called the bias-variance decomposition. This decomposition is a method which examines the expected generalization error for a given learning algorithm and a given data source. This helps us understand questions like: – How can I achieve higher accuracy with my... Read more
10 Minutes to cuDF and Dask cuDF
Centered around Apache Arrow DataFrames on the GPU, RAPIDS is designed to enable end-to-end data science and analytics on GPUs. Together, open source libraries like RAPIDS cuDF and Dask let users process tabular data on GPUs at scale with a familiar, pandas-like API. With Dask, anything you can do... Read more
Nightly News: CI produces latest packages
“Release code early and often” is a software engineering philosophy that RAPIDS takes to heart. We try to release about every six weeks or so, partly to keep up the pace of feature development, but also so RAPIDS users don’t get stuck on older versions of our software for too long.... Read more
Roles & Responsibilities of Artificial Intelligence in Education
Technology has developed by leaps and bounds and it has penetrated into our daily lives in so many ways. It almost seems as if one cannot live without technology because our dependence on it has increased by many folds. Artificial intelligence remains to be a hot topic for the... Read more
Are Successful Data Scientists Hired or Trained?
Editor’s note: Jennifer is a speaker for ODSC West 2019 this November in San Francisco! Be sure to check out her talk, “Successful Enterprise Analytics Starts with Literacy” then! The data science valley of despair is real. Time after time, leaders who’re well-versed in case studies and industry research... Read more
The New Life of the Travel Industry with Artificial Intelligence
The new online opportunities for travelers has a negative influence on touristic companies. A large number of their potential clients prefer to arrange their vacations on the internet instead of going to travel agencies. But there are a lot of ways new technologies, like AI, can actually help travel... Read more
The 4 Most Important Traits to Look for When Hiring an AI Expert
Although AI gets a lot of heat for putting millions of people out of jobs – thanks to its automation properties – it is also creating opportunities for many to start promising careers in data science. Regardless, there can be a lot of roadblocks when hiring an ai expert. ... Read more
How Product Managers Learn About AI Meeting Peak Effectiveness
The most frequent question I get about AI from colleagues, product managers, and others, is, “What do I need to know about AI and what’s the best way to learn it?” I’ve invested a considerable amount of time taking numerous courses, so I dug into my emails to collect... Read more
The Empirical Derivation of the Bayesian Formula
Editor’s note: James is a speaker for ODSC London this November! Be sure to check out his talk, “The How, Why, and When of Replacing Engineering Work with Compute Power” there. Deep learning has been made practical through modern computing power, but it is not the only technique benefiting... Read more